This article discusses the basic capabilities needed to enable robots to operate in human-populated environments for accomplishing both autonomous tasks and human-guided tasks. These capabilities are key to many new emerging robotic applications in service, construction, field, underwater, and space. An important characteristic of these robots is the "assistance" ability they can bring to humans in performing various physical tasks. To interact with humans and operate in their environments, these robots must be provided with the functionality of mobility and manipulation. The article presents developments of models, strategies, and algorithms concerned with a number of autonomous capabilities that are essential for robot operations in human environments. These capabilities include: integrated mobility and manipulation, cooperative skills between multiple robots, interaction ability with humans, and efficient techniques for real-time modification of collision-free path. These capabilities are demonstrated on two holonomic mobile platforms designed and built at Stanford University in collaboration with Oak Ridge National Laboratories and Nomadic Technologies.

A blimp is a small airship that has no metal framework and collapses when deflated. In the first part of this paper, kinematics and dynamics modelling of small autonomous non rigid airships is presented. Euler angles and parameters are used in the formulation of this model. In the second part of the paper, path planning is introduced using helices with vertical axes. Motion generation for trim trajectories (helices with constant curvature and torsion) is presented. Then path planning using helices with quadratic curvature and torsion is described, and motion generation on these helices expressed. This motion generation takes into account the dynamics model presented in the first part.

This paper considers the design of open loop control laws for nonlinear systems that are subject to nonconvex state space constraints. The focus is on finding feasible trajectories for two challenging sets of nonlinear systems: 1) the determination of automobile trajectories through obstacle courses; 2) the design of re-entry trajectories for a reusable launch vehicle model based on the NASA X33 prototype. Our algorithms are based on Rapidly-exploring Random Trees (RRTs) that incrementally explore the state space while satisfying both the global constraints imposed by obstacles and velocity bounds and differential constraints imposed by the equations of motion. The method is particularly suited for high-dimensional problems in which classical numerical approaches such as dynamic programming cannot be applied in practice. Our algorithms for trajectory design have been implemented and evaluated on several challenging examples, which are presented in the paper.

Krzysztof Tchoń, Janusz Jakubiak and Robert Muszyński(Wrocław University of Technology, Poland)

A mobile manipulator is a robotic system composed of a mobile platform and a manipulator mounted atop of the platform. From control theoretic viewpoint the kinematics of the mobile manipulator can be represented by means of a driftless control system with outputs. Assuming this kind of representation we define basic concepts concerned with the kinematics of mobile manipulators and develop a consistent theory involving these concepts in a way completely analogous to the existing theory of stationary manipulators. A key ingredient of our approach is a concept of endogenous configuration of a mobile manipulator that comprises a control function of the platform and a joint position of the manipulator. Relying on this concept we introduce the instantaneous kinematics, analytic Jacobian, regular and singular configurations, a Jacobian pseudoinverse, a dexterity matrix and a dexterity ellipsoid. Then we formulate the inverse kinematic problem (the motion planning problem) for mobile manipulators, and derive two exemplary inverse kinematics algorithms: the Jacobian pseudoinverse (Newton) algorithm and the Jacobian adjoint (Jacobian transpose) algorithm, that are applicable at regular configurations. In a vicinity of singular configurations a version of the singularity robust pseudoinverse is provided. Dexterity ellipsoids and inverse kinematics algorithms are illustrated with computer simulations.

In the paper a solution to the trajectory tracking problem of a mobile manipulator has been presented. By the mobile manipulator we mean a holonomic rigid manipulator mounted on a nonholonomic wheeled mobile platform. First, new control algorithms (which are in fact some modifications of known control algorithms for rigid manipulators) for the dynamics of the mobile manipulator have been introduced, and their convergence proved. Next, we show simulation results which illustrate the behaviour of the mobile manipulator subject to a control action using different control algorithms for the dynamics and the kinematics of an RTR manipulator mounted on the platform of the class (2,0).

This study deals with the problem of tracking a prescribed geometric path by the end-effector of a kinematically redundant manipulator at the control-loop level. During the robot motion, the control constraints resulting from the physical abilities of robot actuators are taken into account. The Lyapunov stability theory is used to derive the control scheme. The numerical simulation results carried out for a planar manipulator whose end-effector tracks a segment line in a two-dimensional work space, illustrate the trajectory performance of the proposed control scheme.

This paper presents a general method for the determination of the identifiable parameters for the geometric calibration of parallel robots. The special case of Stewart-Gough 6 degrees-of-freedom robot is considered in this paper. But this method can be applied for the other structures of parallel robots. The identifiable parameters of various calibration methods are given. Once the identifiable parameters are determined, we can deduce the corresponding physical identification. The method is based on QR decomposition of the observation matrix of the calibration equations. The proposed algorithm can also provide the grouping relations of the non-identifiable parameters with the identifiable parameters.